Continuous, non-invasive assessment of agitation in dementia using inertial body sensors

  • Authors:
  • Azziza Bankole;Martha Anderson;Aubrey Knight;Kyunghui Oh;Tonya Smith-Jackson;Mark A. Hanson;Adam T. Barth;John Lach

  • Affiliations:
  • Virginia Tech Carilion School of Medicine, Roanoke, VA;Virginia Tech Carilion School of Medicine, Roanoke, VA;Virginia Tech Carilion School of Medicine, Roanoke, VA;Virginia Tech, Blacksburg, VA;Virginia Tech, Blacksburg, VA;Wireless Health Interactive, LLC, Vienna, VA;University of Virginia, Charlottesville, VA;University of Virginia, Charlottesville, VA

  • Venue:
  • Proceedings of the 2nd Conference on Wireless Health
  • Year:
  • 2011

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Abstract

Agitated behavior is one of the most frequent reasons that patients with dementia are placed in long-term care settings. These behaviors are indicators of distress and are associated with increased risk of injury to the patients and their caregivers. This study aims to explore the ability of a custom inertial wireless body sensor network (BSN) to objectively detect and quantify agitation, validating against currently accepted subjective clinical measures -- the Cohen-Mansfield Agitation Inventory (CMAI) and the Aggressive Behavior Scale (ABS) -- within the nursing home setting. The ultimate goal is to enable continuous, real-time monitoring of physical agitation in any location over an extended period. Continuous, longitudinal assessment facilitates timely response to agitation events in order to minimize patient distress and risk for injury, to more appropriately titrate pharmacotherapy, and to enable staff (or caregivers) to successfully intervene. Six patients identified as being at high risk for agitated behaviors were enrolled in this pilot study. Patients underwent a series of the above validated tests of memory and agitation. The BSN nodes were applied at three sites on body for three hours while behaviors were annotated simultaneously. This process was subsequently repeated twice for each enrolled subject. The BSN data was then processed using Teager energy analysis, which an earlier study suggested was a promising method for extracting jerky and repetitive movements from inertial data. Results based on construct validity testing for agitation (CMAI) and aggression (ABS) were promising and suggest that additional study with larger sample sizes is warranted.